Method of analysing cell samples, by creating and analysing a resultant image

ABSTRACT

A method is provided for comparing multiple samples of cell extract containing a plurality of components. The method comprises the steps of preparing at least two samples of cell extract from at least two groups of cells and of exposing each of said sample of said cell extract to a different one of a set of matched markers, e.g. luminescent markers, to bind the marker to the cell extract to label the cell extract, each marker within said set of markers being capable of binding to the cell extract and can be individually detected from all other markers within said set. The samples are then mixed to form a mixture and said mixture is electrophoresed to separate the components within the cell extract. At least two electronic images of the electrophoresed mixture are obtained (I) by detection of the individual markers, each image being represented by detection of a marker different from the others. One resultant electronic image (I res ) of the obtained at least two electronic images is created (II) and analyzed in order to identify spot analysis areas (III). The identified spot analysis areas are applied on the respective at least two electronic images for evaluating said areas in order to detect spots representing components of said cell extracts (IV).

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.10/129,448 filed Aug. 27, 2002, now U.S. Pat. No. 7,155,050, which is afiling under 35 U.S.C. §371 and claims priority to international patentapplication number PCT/SE00/02124 filed Oct. 31, 2000, published on May10, 2001, as WO 01/33573, which claims priority to application number9903988-5 filed in Sweden on Nov. 3, 1999; the disclosures of which areincorporated herein by reference in their entireties.

FIELD OF THE INVENTION

The present invention relates to a method of comparing multiple samplesof cell extracts for detecting differences in the protein composition ofcells and cells extracts, and more particularly, to a method utilizingmatched pair of labeling reagents for detecting such differences. By theexpression samples of cell extracts is meant any sample that can besubject to the analysis method outlined in the present application.

BACKGROUND OF THE INVENTION

Researchers studying various aspects of cell biology use a variety oftools to detect and monitor differences in cell structure, function anddevelopment. An essential part of studying cells is studying thedifferences and similarities in the protein composition between thedifferent cell types, stages of development and condition. Determiningdifferences in the protein content between normal and cancerous cells orwild type and mutant cells, for example, can be a valuable source ofinformation and a valuable diagnostic tool.

Mixtures of proteins can be separated into individual componentsaccording to differences in mass by electrophoresing in a polyacrylamidegel under denaturing conditions. One dimensional and two dimensional gelelectrophoresis have become standard tools for studying proteins. Onedimensional SDS (sodium dodecyl sulfate) electrophoresis through acylindrical or slab gel reveals only the major proteins present in asample tested. Two dimensional polyacrylamide gel electrophoresis (2DPAGE), which separates proteins by isoelectric focusing, i.e., bycharge, in one dimension and by size in the second dimension, is themore sensitive method of separation and will provide resolution of mostof the proteins in a sample.

The proteins migrate in one- or two-dimensional gels as bands or spots,respectively. The separated proteins are visualized by a variety ofmethods; by staining with a protein specific dye, by protein mediatedsilver precipitation, autoradiographic detection of radioactivelylabeled protein, and by covalent attachment of fluorescent compounds.The latter method has been heretofore only able to be performed afterthe isoelectric focusing step of 2D PAGE. Immediately following theelectrophoresis, the resulting gel patterns may be visualized by eye,photographically or by electronic image capture, for example, by using acooled charge-coupled device (CCD) or a laser based image detector.

To compare samples of proteins from different cells or different stagesof cell development by conventional methods, each different sample ispresently run on separate lanes of a one dimensional gel or separate twodimensional gels. Comparison is by visual examination or electronicimaging, for example, by computer-aided image analysis of digitized oneor two dimensional gels.

However, each different sample in the separate gels must be preparedwith exacting precision because no two gels are identical, the gels maydiffer one from the other in pH gradients or uniformity. Theelectrophoresis conditions from one run to the next may be different.

The drawbacks by running separate gels are partly overcome by a processdisclosed in WO96/33406, entitled “Difference gel electrophoresis usingmatched multiple dyes”, which is incorporated herein in its entirety.According to this known process the differences between multiple samplesof proteins extracted for example, from different cells, are detected bylabeling each sample of such proteins with a different one of a set ofmatched luminescent dyes. The matched dyes have generally the same ionicand pH characteristics but absorb and/or fluoresce light at differentwavelengths, producing a different color fluorescence. In addition, thedyes should be similar in size. The thus labeled samples are then mixedtogether and co-electrophoresed on a single gel. The proteins common toeach sample comigrate to the same position. Proteins that are differentwill migrate alone to different locations on the gel and will fluorescedifferent colors, thereby identifying which initial sample has one ormore proteins which differ from the initial sample or samples.

The gel can be analyzed by a two (or more) wavelength fluorescencescanner, by a fluorescent microscope or by any known means for detectingfluorescence. An electronic detection system such as a laser scanningsystem with a photo multiplier tube or a charged-coupled device (CCD)camera and a white light source or light sources having predeterminedwavelengths, two electronic images are made of the wet gel usingdifferent known filter sets to accommodate the different spectralcharacteristics of the labels. One image views fluorescence of the firstdye using a first filter appropriate to filter out all light except thatemitted at the wavelength of the first dye and the other image viewsfluorescence of the second dye using a second filter, appropriate tofilter out all light except that emitted at the wavelength of the seconddye. Exposure is about from a few milliseconds to 500 seconds. Eachimage can be considered as a grid-like array of pixel intensity values.

The thus obtained images are then analyzed according to WO96/33406 by acommercially available software package that either will subtract thefirst image from the second to identify spots that are different, or,alternatively, the images may be divided to leave only the spots notcommon to both images. In subtracting the images, like spots will canceleach other, leaving only those that are different. In ratio analysis,like spots will provide a value of one. Differences will result invalues greater than one or less than one.

The above described analysis step in the method known from theWO96/33406 is sometimes very time-consuming.

The traditional method of 2D gel analysis applied on the electronicimages obtained according to the technique disclosed in WO96/33406 mayalso be used. According to this technique each electronic image isindividually analyzed in order to detect spots. Corresponding spots fromthe two images are then matched, compared and further analyzed.

Several drawbacks can be identified using the traditional method whenanalyzing the electronic images.

One drawback is the risks that spots are mismatched, i.e. spots believedto be corresponding in the two images are not. A reason to that may bethat the detection of the electronic image is performed by a sensitivitythat is too low, i.e. exactly the same spots are not detected in bothimages.

Another drawback might be that the further analyses, e.g. calculation ofthe differential expression between the two spots, have some inaccuracy.This is due to that a parameter related to a spot is not calculated inexactly the same way in the two images, e.g. a volume that represents aspot is determined by integration of an analysis area having differentboundaries in the two images.

The matching procedure, shortly described above, is also a tedious andinteractive process introducing variation in results depending on who isperforming the interactive steps.

The object of the present invention is to achieve a less time-consumingmethod of evaluating the electronic images obtained from theelectrophoresed mixture. Another object of the present invention is toachieve a higher degree of accuracy in the analysis of the electronicimages where spots representing components of the cell extracts aredetected.

One further object of the invention is to provide a method that is userfriendly in that only few parameters need to be set in order to performthe measurements. This in turn will result in that the variation of theresult of the measurements between users will be eliminated.

Still another object of the invention is to achieve a higher degree ofautomation when performing the measurements according to the invention.

And still another object of the present invention is that the resultsobtained by using the method will be considered highly reliable.

SUMMARY OF THE INVENTION

The above-mentioned objects are achieved according to the presentinvention by a method having characterizing steps set forth in theindependent claim. Preferred embodiments are set forth in the dependentclaims.

A great advantage with the method according to the invention is that theevaluation of the electronic images representing cell extracts can bepreformed with a higher accuracy since exactly the same spot analysisarea is used, applied exactly at the same location at the respectiveelectronic images. The concept itself ensures that no miss-matchesoccur, i.e. the differential expression between corresponding spots indifferent images can be determined with a higher degree of accuracy.

Even very faint spots can be detected since a spot analysis area pointsout areas where a spot is supposed to be.

Furthermore, if no spot is found in the spot analysis area internalparameters related to the sensitivity in the analysis equipment canautomatically be adjusted.

According to a preferred embodiment of the invention an alignment stepis performed before the resultant electronic image is obtained.

In order to clearly illustrate the principles of the invention it isdescribed in connection with an electrophoresis process. However, theinvention is equally applicable in any 1- or 2-dimensional differentialanalysis method using other separation parameters than pH (charge) andsize. Among these methods are “high pressure liquid chromatography”(hplc) and “cell sorting”.

To illustrate how less time-consuming the analysis performed by themethod according to the present invention compared to a correspondinganalysis performed by conventional technique is, the following exampleis given: A batch of 20 gels of samples takes about one month for oneman to analyze using the old technique. Using the method according tothe present invention the corresponding analysis can be performed inless than one day.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of the process according to the prior art.

FIG. 2 is a flow diagram illustrating the method according to theinvention.

FIG. 3 is flow diagram illustrating important steps of the methodaccording to the invention.

FIG. 4A discloses a two-dimensional representation of a number of pixelintensity values in two electronic images.

FIG. 4B discloses a two-dimensional representation of a number of pixelintensity values illustrating the degree of similarity.

FIG. 5 shows a data display illustrating the method according to theinvention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 2 shows flow diagram illustrating the method according to theinvention. The different steps illustrated in the flow diagram aredescribed below with references to all the figures.

Throughout the description, in the example illustrating the invention isthe separation step preferably performed by electrophoresis. However,the invention is equally applicable in any other separation method.

Preparation and Mixing Step

According to a preferred embodiment of the invention the process of thepresent invention employs a matched set of dyes wherein each dye in theset is generally equal to the other dyes in ionic and pHcharacteristics, and chemical reactivity for covalent attachment toproteins, yet fluoresces at a different wavelength, thereby exhibiting adifferent color luminescence when viewed. The dyes are preferablyroughly equal in molecular weight, but need not be. Each one of the dyeswithin the matched set of dyes is used to label proteins in a differentone of a set of different samples of cell extract so that each cellextract sample is labeled with a different dye within the set of dyes.After labeling, the extracts are mixed and electrophoresed in the samegel, either by one or two-dimensional electrophoresis.

The process described below discloses, for sake of simplicity, only twodifferent cell extracts to be analyzed according to the presentinvention. It should however be noted that the process also isapplicable to any higher number of cell extracts. With references to theschematic diagram of FIG. 1, a first cell extract is prepared by knowntechniques from a first group of cells 1, then labeled with the firstdye of a matched pair of dyes, such as propyl Cyanine (3)-NHS. A secondcell extract is prepared by known techniques from a second group ofcells 2 then labeled with the second dye of the matched pair of dyes,such as methyl-Cyanine (5)-NHS. The structures and methods ofpreparation of the cyanine (3) and (5) are described in theabove-mentioned WO96/33406. To label the cell extract mixture, thereactive form of the dye and the protein extract are incubated in asuitable container, such as a test tube 3 for a time sufficient to allowfor the formation of a covalent bond between the reactive form of thedye and potential attachment or binding sites on the proteins in theextract. The period of time is generally from 15 to 30 minutes,depending on the temperature. The temperature range is generally fromabout 0° C. to 25° C. The reaction between the dye and the proteins maybe quenched after a sufficient percentage of available binding sites onthe protein molecule are covalently bound to the dye. Any suitable knownquenching material may be used.

The first and second group of cells (1,2) can be any two sets of cellsthe protein content of which one wishes to compare or contrast. Forexample, the first group of cells can be the wild-type, or normal,cells, and the second group of cells can be mutant cells from the samespecies. Alternatively, the first group of cells can be normal cells andthe second group can be cancerous cells from the same individual. Cellsfrom the same individual at different stages of development or differentphases of the cell cycle can be used also.

The differences in protein composition between cells of the same typefrom different species can also be the subject of study by the processof the present invention. In addition, the process of the presentinvention can be used to monitor how cells respond to a variety ofstimuli or drugs. All of the events that might alter cell behavior asexpressed through protein changes, that includes modifications toproteins such as “Post Translational Modification” (PTM), can bedetected without the need and expense of high precision 2D PAGE systems.Those skilled in the art will recognize that the proteins for comparisonmay also be derived from biological fluids, such as serum, urine, spinalfluid, bacterial, mammalian, or plants etc.

Although the preferred embodiment of the invention is illustrated by anexample where the cell extract is labeled by a fluorescent dye theinvention is equally applicable when analyzing cell extract labeled byother identifying labels. WO98/23950 discloses a number of alternativelabels, e.g. by metabolic labeling with any suitable radionuclide (e.g.tritium, a radionuclide of sulfur or a radionuclide of carbon) or bychemical or enzymatic labeling with any suitable radionuclide (e.g.radio-iodine). It is also possible to use any stable naturally occurringisotope. The thus labeled proteins are imaged with any detector that iscapable of detecting the label used. For instance by using densitometryor spectroscopy, or by detecting radioactivity.

Electrophoresis Step

The labeled samples are mixed and, as illustrated in FIG. 1, applied inmeasure aliquots to one gel 4, then preferably subjected to 2D PAGE. Onedimensional SDS electrophoresis can be used instead of 2D PAGE. Theprocedures for running one dimensional and two dimensionalelectrophoresis are well known to those skilled in the art.

Proteins that the two cell groups have in common form coincident spots6. The fluorescent intensity from identical proteins from either groupwill theoretically be the same for the vast majority of proteins.Proteins that the two groups do not have in common 8,9 will migrateindependently. Thus, a protein that is unique or of different relativeconcentration to one group will have a different fluorescence intensity.

As described above in relation to the known technique according toWO96/33406 the gel can be analyzed by a two wavelength fluorescencescanner, by a fluorescent microscope or by any known means for detectingfluorescence. Two electronic images are made of the wet gel usingdifferent known filter sets to accommodate the different spectralcharacteristics of the labels. Each electronic image can be consideredas a grid-like array of pixel intensity values, electronic image I₁ withpixel intensity values p₁, . . . , p_(N), and electronic image I₂ withpixel intensity values p′₁, . . . , p′_(N).

Alignment Step

According to a preferred embodiment of the invention is an alignmentstep performed before a resultant electronic image is created. This stepis optional and is only performed if considered necessary.

Although the electrophoresis of the two different cell samples isperformed in the same gel and mismatches between different gels areavoided is it often considered necessary to perform an alignment stepbefore creating the resultant electronic image. The reason is that themarkers used, e.g. luminescent markers, as labels on the cell extractsmight under certain circumstances influence some characteristics, e.g.the size, of the molecules of the cell extract. The object of thealignment step is to ensure that corresponding pixel intensity values,i.e. pixel intensity values representing the same spot, e.g. the sameprotein, coincide in the resultant image.

The pixel intensity values of the two electronic images are compared toeach other using conventional image analysis methods in order to checkif patterns on one image coincide with corresponding patterns on theother image. Applying e.g. a cross correlation function when comparingthe intensity values in predetermined limited areas of the two images isone obvious way to perform this. The cross correlation function providesa score value indicating the degree of alignment between the two images.

One result of this initial comparison could be that the electronicimages already are aligned to each other and in that case no alignmentis necessary.

If the images are not aligned to an acceptable degree several differentalignment sub-steps can be performed:

Aligning the electronic images with respect to each other.

Applying a linear transformation.

Applying a more complex stretching function.

Each sub-step can be used alone or in combination with one or all othersteps.

The alignment can be performed in two dimensions. The electronic imagesare continuously compared to each other during the alignment step.

Combining Step

A presumption for achieving a good overall result of the methodaccording to the invention is naturally that the alignment between theelectronic images is good so that pixel intensity values at the samelocation in the two electronic images really represent the same spot inrespective cell sample (only of course when no changes that influencethe proteins have occurred between the samples). Two aligned electronicimages can be seen in FIG. 3, step I. As can be seen are they slightlydifferent in that one of the spots is missing in the other image.

One resultant electronic image (I_(res)) is created of the obtained twoelectronic images by combining corresponding pixel intensity values p₁,. . . , p_(N), and p′₁, . . . , p′_(N) from the electronic images I₁ andI₂, respectively, according to a predetermined function. Step II in FIG.3. One straightforward way of combining the pixel intensity values isachieved by forming the sum of corresponding pixel intensity values,e.g. p_(1res)=(p₁+p′₁)/2.

Another way of calculating the resulting intensity values is achieved byp_(1res)=√{square root over (p₁ ²+p′₁ ²)}.

A more general and complex function can of course be used whencalculating a resultant intensity value, e.g. taking into accountadjacent intensity values or taking into account an average of all or asubset of pixel intensity values.

A resultant electronic image I_(res) thus obtained comprises a grid-likearray of resultant pixel intensity values p_(1res) . . . p_(Nres).

Analysis of Resultant Image

The resultant image is then analyzed in order to identify spot analysisareas.

Different methods of analyzing images represented by pixel values inorder to group them into spot analysis areas according to predeterminedcriteria are well known to persons skilled in the art. One class ofalgorithms that can be used is described in “A new segmentation andmodeling algorithm for electrophoresis gels” by E. Battens et al,Electrophoresis 1997, 18, pp. 793-798.

Another class of algorithms that also can be used is based on so-callededge detection, which is a well-known pattern detection algorithm.

According to a preferred embodiment of the invention the number of spotanalysis areas to be identified in the resultant image is set to apredetermined value, e.g. 800. That value can be regarded as a level ofsensitivity in that the e.g. 800 best spot analysis areas, according toa predefined scoring function, where the score is based on a set ofsuitable spot features are extracted.

It should especially be noted in a preferred embodiment of the inventionthat the number of spot analysis areas preferably is the only parameterto be set when the spot analysis areas are identified.

The predetermined value can of course be set to any appropriate value.

Analysis of Spot Analysis Areas.

It is sometimes necessary to analyze the spot analysis areas before theyare applied on the electronic images. The reason is to ensure that theanalysis areas represent a true protein spot and not is the result of anunpredictable artifact, e.g. dirt or dust. If the analysis of the spotanalysis areas indicate that an area not represents a true protein spotthat area is classified as an artifact in order to make it possible toexclude that area from the further method steps. The areas classified asartifacts are still available if considered necessary to further analyzethem.

There are many criteria that can be applied in order to identify trueprotein spots. Among those can be mentioned the size of a spot analysisarea and the three dimensional topography of a spot analysis area wherethe degree of edginess in the area is determined by applying e.g. theLaplace-filtration method, which is a well-known method for filtrationof three dimensional objects. For instance is a dust particle identifiedin that it has a much more erratic and narrow edge compared to the muchsmoother curve form of a true protein spot.

A normalization of the identified true protein spot features with regardto a corresponding “mean” feature for a subset of all spots whereobvious outliers have been removed is performed. Limits are thendetermined in order to classify the spots in relation to the normalizedfeatures.

Another method of identifying true protein spots is to apply anartificial neural network, which is during a learning process “learned”how to identify true protein spots when fed with normalized featuresmentioned above.

The analysis and filtration described above may be regarded as a dustfiltering step.

Apply Spot Analysis Areas on Electronic Images

The thus obtained spot analysis areas are then applied on the electronicimages, in this example images I₁ and I₂. Step IV in FIG. 3. It isimportant to notice that the same spot analysis areas are applied onboth images. If the images have been aligned (aligned, stretched etc.)to each other prior the combining step it is of course the alignedelectronic images that are used during the further analysis.

FIG. 4 illustrates a great advantage that is achieved by using the sameareas on both images.

In FIG. 4 is disclosed a two-dimensional representation of a number ofpixel intensity values along one row of the arrays in images I₁ and I₂,respectively. One way of analyzing these images is to determine the areabelow the curve represented by the peak values of the intensity values,above a predetermined base level (B) and between x₁ and x₂ in thefigure. Although the maximum amplitude of the curve differs between theimages the contribution from image I₂ is substantial. In particular incases where spot represented by the curve in image I₂ is so faint thatit should hardly be detected at all using the technique according to theprior art.

When analyzing the images the volume of a so-called 3D map in the spotanalysis areas is determined as illustrated in FIG. 5, “3D spot view”. A3D map is a three dimensional representation of the pixel intensityvalues of an electronic image of an electrophoresed cell sample.

Determine Degree of Similarity

According to a preferred embodiment of the invention is the degree ofsimilarity between corresponding spot analysis areas in two (or more)images determined. With the expression similarity is here meant thesimilarity between corresponding spot analysis areas regarding the3-dimensional curve-form. To further illustrate this is shown in FIG. 4Ba representation of two different spot analysis areas applied on twoelectronic images. It must be observed that FIG. 4B only shows a twodimensional representation of a two dimensional slice of a spot analysisarea represented by a row of pixel intensity values in order toillustrate the principle. When determining the degree of similarity itis applied in three dimensions on all pixel intensity values of a spotanalysis area.

The left curves show a spot analysis area from the two images having alow degree of similarity, i.e. the curves are not similar to each other.This may be interpreted as an indication that there is some uncertaintyregarding the analysis of this spot analysis area that may affect thefurther analysis. This uncertainty must sometimes be further analyzedand can be related to the identity of the protein represented by thepixel intensity values of the analysis area; to post translationalmodifications of the proteins or to unidentified problems regarding theelectrophorsis.

The right curves show a spot analysis area from the two images having ahigh degree of similarity, i.e. the curves are similar to each other. Inthis case the result of the determined degree of similarity ensures thatthe identity of the protein represented by the pixel intensity values ofthe analysis area can be determined and the further analysis can beperformed with a higher degree of accuracy.

There are many different ways of determining the above-mentioned degreeof similarity between the curve forms.

According to a preferred embodiment of the invention is the so-called“Pearson Correlation Method” used, which is well known to personsskilled in the art, to determine the value representing the degree ofsimilarity. Other more general methods may also be used.

Among those can be mentioned performing normalization with regard to thepixel intensity values and to the size of the spot analysis area anddetermining the squared values of the differences between thecorresponding pixel intensity values.

It should be noted that the degree of similarity does not depend of theamplitude of the three-dimensional curve-forms but of the similarity ofthe curve forms, which is illustrated in FIG. 4B.

The result of this step is a measure of the degree of similarity,whereas e.g. a measure close to 1 represents high degree of similarityand values less than 1 indicates lower degree of similarity.

A presumption for determining the degree of similarity that provides thehigher degree of accuracy as mentioned above is that the spot analysisareas are determined according to the steps outlined above.

Determine Differential Expression

According to established technique a method of analyzing imagesrepresenting detected spots of cell samples in order to comparecorresponding detected spots a so-called differential expression DEbetween predetermined parameters of the detected spots is determined.The differential expression is defined as

${DE} = {\frac{B_{quantity}}{A_{quantity}}.}$B_(quantity) and A_(quantity), respectively, are e.g. determined as thevolume within each spot analysis area as indicated above.

DE indicates changes to the spots between the images. If DE is near 1 itmay be concluded that no changes have occurred.

The differential expressions of a pair of electronic images arecalculated and can be arranged in a histogram as shown in FIG. 5, “Spotselection”. In a situation where the majority of the proteins areunchanged between the two images all the spots have almost the same DE,resulting in a histogram curve having the majority number of spots closeto the same DE. In an ideal situation, i.e. the two samples have exactlythe same number of protein molecules in each cell sample, the DEtheoretically is 1 when no changes have occurred with the proteins.However, due to many factors, a systematic deviation of the pixelintensity values might result in that the maximum amplitude of thehistogram curve differs from 1.

A histogram curve corrected in respect of any systematic errors can beprovided in many different ways. The set of differential expressionscould be normalized with respect to the mean value of the DEs. Thenormalized set of DEs could then be used to arrange a normalizedhistogram curve. Another way is to identify the maximum amplitude of thehistogram curve and to define corresponding DE as 1.

The spots represented by a DE that differs from 1 in a correctedhistogram curve can then easily be identified and further analyzed.

As can be seen in the data display of the histogram in FIG. 5 limits canbe applied in order to sort out under or over expressed spots. Thelimits may be chosen such that a predetermined percentage of the spotsare regarded as under or over expressed. A Gauss curve may also beapplied and adjusted to correspond to the histogram curve in order toperform the further analysis.

Data Display

FIG. 5 shows a data display illustrating the method according to theinvention. As can be seen is the display divided in four differentviews: “Image view”, “Spot selection”, “3D spot view” and a “Resulttable”. All these views are linked so that if e.g. a spot pair is chosen(pointed at) on the Image view it is at the same time seen at the 3Dspot view and marked in the “differential expression histogram” in theSpot selection view and in the Result table. It is of course alsopossible to choose a particular pair of spots in the result table whichthan at the same time are highlighted in the others views.

One feature of the Spot selection view of the data display worthmentioning is the possibility of changing the parameter used on thevertical axis. It is thus possible to choose a specific pair of spots inthe Spot selection view having a differential expression indicated onthe horizontal axis and e.g. the area, volume or the degree ofsimilarity indicated on the vertical axis. This feature is especiallypowerful when analyzing pair of spots with a differential expressiondifferent from the majority of pair of spots. It is then possible toeasily obtain values of the different above-mentioned parameters inorder to analyze more accurately the specific pair of spots.

As indicated above all or some steps of the method according to theinvention are also applicable in one-dimensional separation methods,e.g. one-dimensional electrophoresis.

All steps described above may be performed in a fully automated processhaving the capability of being loaded with analysis data from manydifferent samples and capable of performing concurrent analysis on allthese data.

The above examples illustrate specific aspects of the present inventionand are not intended to limit the scope thereof in any respect andshould not be so construed. Those skilled in the art having the benefitof the teachings of the present invention as set forth above, can effectnumerous modifications thereto. These modifications are to be construedas being encompassed within the scope of the present invention as setforth in the appended claims.

1. A method of comparing multiple samples of cell extract containing aplurality of components comprising: preparing at least two samples ofcell extracts from at least two groups of cells; exposing each of saidat least two samples of said cell extracts to at least one differentmarker of a set of matched markers to bind the at least one differentmarker to the cell extracts to label the cell extracts, each markerwithin said set of matched markers being capable of binding to the cellextracts and can be individually detected from all other markers withinsaid set of matched markers; mixing said at least two samples of thelabeled cell extracts to form a mixture; separating said mixture toseparate a plurality of components within the cell extracts; obtainingat least two electronic images of the separated mixture by detectionof-individual markers in the set of matched markers, each image beingrepresented by detection of the at least one different marker that isunique from the set of matched markers; creating one resultantelectronic image (I_(res)) of the obtained at least two electronicimages; analyzing the resultant image in order to identify spot analysisareas; and applying said identified spot analysis areas on each one ofthe at least two electronic images for evaluating said identified spotanalysis areas in order to detect spots representing the plurality ofcomponents of said cell extracts.
 2. The method of claim 1, whereinseparating said mixture is performed by electrophoresis.
 3. The methodof claim 2, wherein said set of matched markers are a luminescent set ofdyes that covalently bind at least one dye to the cell extracts to labelthe cell extracts, each dye within said luminescent set of dyes beingcapable of covalently binding to the cell extracts and having generallya similar ionic and pH characteristics as all other dyes with theluminescent set of dyes within said set of dyes and emitting light at awavelength sufficiently different from all other dyes within said set ofdyes to present a different colored light.
 4. The method of claim 1,further comprising: determining a degree of similarity between pixelintensity values in the applied said identified spot analysis areas inthe two electronic images.
 5. The method of claim 4, wherein said degreeof similarity is determined by a Pearson Correlation method.
 6. Themethod of claim 1, wherein a number of the identified spot analysisareas in the one resultant electronic image is set to a predeterminedvalue.
 7. The method of claim 1, wherein the identified spot analysisareas are subjected to filtration in order to classify the identifiedspot analysis areas according to a predetermined criteria related to athree dimensional topography of said identified spot analysis areas. 8.The method of claim 1, further comprising: comparing correspondingdetected spots by forming a differential expression (DE) betweenpredetermined parameters of said detected spots.
 9. The method of claim7, wherein the differential expressions are normalised and arranged in ahistogram.
 10. The method of claim 9, wherein predetermined limitsrepresenting under and over expressed the corresponding detected spotsare set in the histogram.
 11. The method of claim 10, wherein accordingto said predetermined function each of the corresponding pixel intensityvalues are determined as$p_{1\;{res}} = {\sqrt{p_{1}^{2} + p_{1}^{\prime 2}}.}$
 12. The methodof claim 1, further comprising: providing an alignment to be performedbefore creating the resultant electronic image (I_(res)) in order toalign the electronic images so that the spots coincide.
 13. The methodof claim 12, further comprising: aligning the at least two electronicimages with respect to each other.
 14. The method of claim 1, whereinpreparing the at least two samples is controlled by a user interfacedisplay comprising a predetermined number of predefined changeableviews, all simultaneously available, each being a graphical or anumerical representation of different steps performed, wherein saidnumerical representation comprises graphical or numerical objects of thedetected spots or the identified spot analysis areas, wherecorresponding objects are linked together in different views.
 15. Themethod of claim 6, wherein the predetermined value is
 800. 16. Themethod of claim 1, wherein creating one resultant electronic image(I_(res)) of the obtained at least two electronic images is achieved bycombining corresponding pixel intensity values (p₁, . . . , p_(2N); p′₁,. . . , p′_(N)) according to a predetermined function.
 17. The method ofclaim 16, wherein said predetermined function is a summation(p_(1res)=(p₁+p′₁)/2) of the corresponding pixel intensity values. 18.The method of claim 12, further comprising: applying a lineartransformation.
 19. The method of claim 12, further comprising: applyinga stretching function.